Here are 28 books that Data Sketches fans have personally recommended if you like
Data Sketches.
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I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
It is not enough for a data scientist to be able to analyze data and build ML models. You have to be able to communicate the insights to decision-makers concisely and accurately. This book shows you bad and good visualizations — you’ll be surprised by how often you would have defaulted to the bad way without the guidance provided by this book!
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options.
This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke…
I am a leader in analytics and AI strategy, and have a broad range of experience in aviation, energy, financial services, and the public sector. I have worked with several major organizations to help them establish a leadership position in data science and to unlock real business value using advanced analytics.
Data scientists and analytics specialists are great at building models and algorithms, but often wrap them in a presentation or dashboard that diminishes their value and reduces the likelihood of their work being adopted. This book encourages practitioners to always consider the last mile and to pay as much attention to presentation and aesthetics as we do to the model itself.
Master the art and science of data storytelling-with frameworks and techniques to help you craft compelling stories with data.
The ability to effectively communicate with data is no longer a luxury in today's economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative-to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories.
Narratives are more powerful than raw statistics, more enduring than pretty charts. When…
In sixth grade, my teacher tried to teach the class how to read line charts – and something fell into place for me. Ever since then, I’ve tried to sort data into forms that we can use to make sense of it. As a researcher at Microsoft, I consulted with teams across the organization – from sales to legal; and from Excel to XBox – to help them understand their data. At Honeycomb, I design tools for software operations teams to diagnose their complex systems. These books each gave me an “ah-hah” moment that made me think differently about the craft of creating visualization. They now sit on my shelf in easy reach – I hope you find them fascinating too.
A new edition of Bertin’s 1963 Semiology was released a few years ago, and my heart swelled with joy. For years, I’d worked off of bad photocopies of an inter-library loan book that had long since gone out of print. In this new edition, I could see how Bertin works through different dimensions and axes – when you want to plot two different quantitative axes over a map, what are your choices? What if you want to plot them over a graph, instead? What changes? I loved exploring these choices with Bertin, as he explores how different color mappings, iconic representations, and design choices change the way the reader interprets the graph.
Originally published in French in 1967, Semiology of Graphics is internationally recognized as a foundational work in the fields of design and cartography. Based on Jacques Bertin's practical experience as a cartographer, part one of this work is an unprecedented attempt to synthesize principles of graphic communication with the logic of standard rules applied to writing and topography. Part two brings Bertin's theory to life, presenting a close study of graphic techniques, including shape, orientation, colour, texture, volume, and size, in an array of more than 1,000 maps and diagrams.
I am not very good at making things. I am good enough to appreciate the craftsmanship of those much better than me. I am more of an ideas person, perhaps why I ended up with a PhD in Philosophy of Science. But I have always held a secret admiration—with a tinge of envy—for people who are makers. As I went deeper into my career as a philosopher of science, I became aware that the material/making aspect of science—and technology—was largely ignored by ideas-obsessed philosophers. So, this is where I focused my attention, and I’ve loved vicariously being able to be part of making the world.
When I was a kid, one of my favorite books was The Way Things Work, not the more recent David Macaulay book—which is also good—but the earlier 1967 book by T. Lodewijk. With great diagrams, it showed how complicated machines work.
Randall Munroe's Thing Explainer, while less comprehensive, similarly captures this magic for me. It has great diagrams and simple clarifying text—self-consciously limited to the 1,000 words people use the most. I could stare at the diagrams for hours, learning about everything from cameras (“picture takers”) to submarines (“boats that go under the sea”).
From the No. 1 bestselling author of What If? - the man who created xkcd and explained the laws of science with cartoons - comes a series of brilliantly simple diagrams ('blueprints' if you want to be complicated about it) that show how important things work: from the nuclear bomb to the biro.
It's good to know what the parts of a thing are called, but it's much more interesting to know what they do. Richard Feynman once said that if you can't explain something to a first-year student, you don't really get it. In Thing Explainer, Randall Munroe takes…
I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.
For those intending to use R with an eye on the popular 'Tidyverse' suite of packages – which facilitate the handling, manipulation, and visualisation of data sets – it's hard to go past this book. From the founding contributors of the RStudio/Tidyverse worlds, this is a great way to learn about this dialect of R against the overarching backdrop of statistical data analysis and data science.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along…
Colin Koopman researches and teaches about technology ethics at the University of Oregon, where he is a Professor of Philosophy and Director of the interdisciplinary certificate program in New Media & Culture. His research pursuits have spanned from the history of efforts in the early twentieth century to standardize birth certificates to our understanding of ourselves as effects of the code inscribed into our genes. Koopman is currently at work on a book that will develop our understanding of what it takes to achieve equality and fairness in data systems, tentatively titled Data Equals.
W.E.B. Du Bois is widely acknowledged as the leading activist for racial equality of his generation. But until very recently little had been known of his deep commitment to the pursuit of equality within and through data technology. As Du Bois was preparing notes for his famous 1903 book The Souls of Black Folk, he was also preparing an exposition of what we would today call “infographics” (or what the editors of this volume aptly call “data portraits”) for exhibition at the 1900 Paris Exposition world’s fair. This volume handsomely reproduces for the first time a full-color complete set of Du Bois’s charts, graphs, maps, and ingenious spirals. A beautiful book to live with, it also subtly transforms one’s understanding of the history of racial progress and inequality in America.
"As visually arresting as it is informative."-The Boston Globe
"Du Bois's bold colors and geometric shapes were decades ahead of modernist graphic design in America."-Fast Company's Co.Design
W.E.B. Du Bois's Data Portraits is the first complete publication of W.E.B. Du Bois's groundbreaking charts, graphs, and maps presented at the 1900 Paris Exposition.
Famed sociologist, writer, and Black rights activist W.E.B. Du Bois fundamentally changed the representation of Black Americans with his exhibition of data visualizations at the 1900 Paris Exposition. Beautiful in design and powerful in content, these data portraits make visible a wide spectrum of African American culture, from…
I am a leader in analytics and AI strategy, and have a broad range of experience in aviation, energy, financial services, and the public sector. I have worked with several major organizations to help them establish a leadership position in data science and to unlock real business value using advanced analytics.
Since data science is, at its core, people helping people make decisions, it is essential that we can establish productive relationships with our stakeholders. This is a skill that needs to be given the same level of effort as we give to coding or statistics. Gilbert’s book is a great resource to help technically oriented people to advance their people skills.
"For the engineer, scientist, or technology professional seeking to communicate better in the business world, this is the book you've been craving your entire career!" ” — Douglas Laney, Innovation Fellow, West Monroe, and best-selling author of "Infonomics"
Your analytical skills are incredibly valuable. However, rational thinking alone isn’t enough.
Have you ever:
Presented an idea, but then no one seemed to care?
Explained your analysis, only to leave your colleague confused?
Struggled to work with people who are less analytical and more emotional?
In these situations, people skills make the difference, and research shows these skills are becoming increasingly…
I studied statistics and data science for years before anyone ever suggested to me that these topics might have an ethical dimension, or that my numerical tools were products of human beings with motivations specific to their time and place. I’ve since written about the history and philosophy of mathematical probability and statistics, and I’ve come to understand just how important that historical background is and how critically important it is that the next generation of data scientists understand where these ideas come from and their potential to do harm. I hope anyone who reads these books avoids getting blinkered by the ideas that data = objectivity and that science is morally neutral.
The thing you should know about science is that it’s a human enterprise. As a result, it’s dependent on human factors like social consensus and prejudice. In this series of case studies of famously expensive and difficult-to-replicate experiments probing the limits of scientific understanding from biology to theoretical physics, Collins and Pinch show how scientific knowledge gathering is rarely straightforward because there are always alternative explanations available for the data. Was the phenomenon real or was the experiment set up badly? We can never know for sure, but we decide collectively what we believe. Scientists are experts participating in human culture, they argue, not mysterious clergy issuing declarations of absolute truth.
Harry Collins and Trevor Pinch liken science to the Golem, a creature from Jewish mythology, powerful yet potentially dangerous, a gentle, helpful creature that may yet run amok at any moment. Through a series of intriguing case studies the authors debunk the traditional view that science is the straightforward result of competent theorisation, observation and experimentation. The very well-received first edition generated much debate, reflected in a substantial new Afterword in this second edition, which seeks to place the book in what have become known as 'the science wars'.
I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
Even if you are ultimately going to be working with terabytes of data, you’ll start out doing exploratory data analysis. The tool that you’ll use for that is most likely going to be Pandas. One of the best investments that you can make when becoming a data scientist is to become a Pandas expert, and there is no better book than Harrison’s to help you get there. Plus, many of the interview questions you will face during the hiring process will probably involve Pandas. Blow your interviewers out of the water by showing them corners of the Pandas library they didn’t even know!
Best practices for manipulating data with Pandas. This book will arm you with years of knowledge and experience that are condensed into an easy to follow format. Rather than taking months reading blogs and websites and searching mailing lists and groups, this book will teach you how to write good Pandas code.
It covers:
Series manipulation
Creating columns
Summary statistics
Grouping, pivoting, and cross-tabulation
Time series data
Visualization
Chaining
Debugging code
and more...
Hi, I’m Neil. We need to live our tiny, precious lives with intention. I write about failure, resilience, happiness, trust, and gratitude. I’m the New York Times bestselling author of 10 books and journals that have sold over 2,000,000 copies and spent over 200 weeks on bestseller lists, including The Happiness Equation, Two-Minute Mornings, and You Are Awesome. I host the award-winning, ad-free, sponsor-free podcast 3 Books, where I’m on a 22-year quest to uncover the 1000 most formative books in the world. Guests include Brené Brown, Quentin Tarantino, and David Sedaris. I give over 50 keynote speeches a year at places like Harvard, SXSW, and Microsoft.
If I were teaching a course on life, this would be a mandatory textbook. Talib defines black swan events as events that 1) are disproportionately huge, 2) cannot be predicted, and 3) are mistakenly explained in retrospect with hindsight and fallacies.
This book helped me leave my corporate job and strike out on my own. Why? To help unroll the canvas of myself and my life, so I was more exposed to black swan events, leading me to write more books and have more unlikely, amazing experiences.
The most influential book of the past seventy-five years: a groundbreaking exploration of everything we know about what we don’t know, now with a new section called “On Robustness and Fragility.”
A black swan is a highly improbable event with three principal characteristics: It is unpredictable; it carries a massive impact; and, after the fact, we concoct an explanation that makes it appear less random, and more predictable, than it was. The astonishing success of Google was a black swan; so was 9/11. For Nassim Nicholas Taleb, black swans underlie almost everything about our world, from the rise of religions…
